Network Defense Decision-making Method Based on Improved Evolutionary Game Model

MA Runnian; ZHANG Enning; WANG Gang; MA Yufeng; WENG Jiang

doi:10.11999/JEIT220585

Volume 45 Issue 6

Jun. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(6): 1970-1980

MA Runnian, ZHANG Enning, WANG Gang, MA Yufeng, WENG Jiang. Network Defense Decision-making Method Based on Improved Evolutionary Game Model[J]. Journal of Electronics & Information Technology, 2023, 45(6): 1970-1980. doi: 10.11999/JEIT220585

Citation:

MA Runnian, ZHANG Enning, WANG Gang, MA Yufeng, WENG Jiang. Network Defense Decision-making Method Based on Improved Evolutionary Game Model[J]. Journal of Electronics & Information Technology, 2023, 45(6): 1970-1980. doi: 10.11999/JEIT220585

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Network Defense Decision-making Method Based on Improved Evolutionary Game Model

doi: 10.11999/JEIT220585

1.
Institute of Telecommunication Engineering, Air Force Engineering University, Xi’an 710077, China
2.
Information and Communication Institute Experimental Training Base, National University of Defense Technology, Xi’an 710106, China

Funds: The National Natural Science Foundation of China (61902426)

Received Date: 2022-05-10
Rev Recd Date: 2022-07-16

Available Online: 2022-07-21

Publish Date: 2023-06-10

Abstract

Abstract

For the problem that the existing network defense decision-making method is challenging by error interference and real-time response, a novel network defense decision-making method based on an Improved Evolutionary Game Model (IEGM) is proposed. Firstly, using the classical servo system model for reference, the short-term prediction effect of the defense side on the attack strategy is quantified by differential hypothesis to accelerate the convergence of the model and improve the efficiency of defense decisions. Secondly, the mechanism of error generation in attack-defense game is analyzed, then the observational error in network defense is defined quantitatively, and the improved replication dynamics equation is proposed to strengthen the tolerance of the model to information deviation. On this basis, an improved evolutionary game model is established, and the corresponding stability analysis and mathematical proof are given to prove that the model can converge to the $ \varepsilon $-neighborhood of the Nash equilibrium solution. Theoretical analysis and simulation results show that the proposed model can overcome the influence of observation error, and the optimal pure defense strategy with deviation order of 0.01% is given. Besides, under the jamming environment, the response speed of defense decision-making can be improved by 64.06% compared with the other three decision models. The improved model and decision-making method can effectively improve the response timeliness of defense decisions and the adaptability to observation error.
- Network defense,
- Decision-making method,
- Error tolerance,
- Short-term prediction,
- Improved replicator dynamics

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References(22)

References

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